Data from: Analyzing recreational fishing effort – Gender differences and the impact of Covid-19
Data files
May 15, 2025 version files 228.16 KB
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C01_AASurvey_exemplarydata.csv
214.84 KB
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Create_Evaluate_BN.R
4.77 KB
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README.md
8.55 KB
Abstract
Recreational fishing is an important economic driver and provides multiple social benefits. To predict fishing activity, identifying variables related to variation, such as gender or Covid-19, is helpful. We conducted a Canada-wide email survey of users of an online fishing platform and analyzed responses focusing on gender, the impact of Covid-19, and variables directly related to fishing effort. Genders (90% men and 10% women) significantly differed in demographics, socioeconomic status, and fishing skills but showed similar fishing preferences, fishing effort in terms of trip frequency, and travel distance. Covid-19 altered trip frequency for almost half of fishers, with changes varying by gender and activity level. A Bayesian network revealed travel distance as the main determinant of trip frequency, negatively impacting fishing activity for 61% of fishers, with fishing expertise also playing a role. The results suggest that among active fishers, socio-economic differences between genders do not drive fishing effort, but responses to Covid-19 were gender-specific. Recognizing these patterns is critical for equitable policy-making and accurate socio-ecological models, thereby improving resource management and sustainability.
https://doi.org/10.5061/dryad.1vhhmgr3m
This README file was generated on 2024-09-17 by Julia Sabine Schmid
Files and variables
File: Angler_Survey.pdf (Zenodo - Supplemental information)
Description:
Email survey in the study “Analyzing recreational fishing effort - Gender differences and the impact of Covid-19”
File: C01_AASurvey_exemplarydata.csv
Description:
Exemplary mail survey responses in the study “Analyzing recreational fishing effort - Gender differences and the impact of Covid-19”. Please note that these are not actual survey responses but exemplary data, as participants consented to their data being used solely for the purposes of the related study. This means the dataset was artificially created for demonstration purposes - some columns were randomly shuffled, and the content does not reflect real individual answers.
Date of Data Collection
July 2023 - August 2023
Content Overview
This supplementary file includes the email survey responses as part of the study “Analyzing recreational fishing effort - Gender differences and the impact of Covid-19”.
The raw data was preprocessed according to the methods section of the research paper.\
Missing values (NA) indicate that respondents chose not to provide an answer to the corresponding question.
File Format
Comma-separated values (.csv)
Structure of the File
Each line corresponds to one sample (1,500 samples)
Variables
- TravelDistanceMin (“How far do you typically travel to go fishing?”, smallest selected option):
0: <20km; 1: 20-50km; 2: 50-100km; 3: 100-200km; 4: >200km - TravelDistanceMax (“How far do you typically travel to go fishing?”, largest selected option):
0: <20km; 1: 20-50km; 2: 50-100km; 3: 100-200km; 4: >200km - NShortTrips (“Over the past five years, how many short fishing trips did you go on each year?”):
0: <5 trips; 1: 6-19 trips; 2: >=20 trips - NLongTrips (“Over the past five years, how many long fishing trips did you go on each year?”):\
0: <1 trip; 1: 2-7 trips; 2: >=8 trips - ReportRateTripsAA (“Do you record every fishing trip on the MyCatch app or the Angler’s Atlas website?”):
0: No trips at all; 1: <50%; 2: >50%; 3: All trips - WBPreference (“What kind of water body do you prefer for freshwater fishing?”):
0: River; 1: Small lake; 2: Big lake; 3: Not important - BusyOrQuiet (“Do you prefer busy or quiet places to fish?”):
0: Not important, 1: Quiet; 2: Busy - ShoreOrBoat (“Do you usually fish from the shore or a boat?”):
0: Both; 1: Boat; 2: Shore - Work (“What is your employment status?”):
0: Employed full time; 1: Retired; 2: Employed part time; 3: Unemployed; 4: On disability - Vehicle (“Do you own or have easy access to a vehicle?”):
0: Yes; 1: No; 2: Sometimes - Boat (“Do you own or have easy access to a boat?”):
0: Yes; 1: No; 2: Sometimes - OceanFishing (“Do you also go fishing in the ocean?”):
0: No; 1: Yes, but preferably freshwater fishing; 2: Yes, mainly in the ocean - ImpactHotWeather (part of “How will these factors influence your fishing?”):
0: Doesn’t matter; 1: Might cancel fishing; 2: Might go fishing; 3: Usually cancel fishing; 4: Usually go fishing - ImpactRainyWeather (part of “How will these factors influence your fishing?”):
0: Doesn’t matter; 1: Might cancel fishing; 2: Might go fishing; 3: Usually cancel fishing; 4: Usually go fishing - ImpactWindy (part of “How will these factors influence your fishing?”):
0: Doesn’t matter; 1: Might cancel fishing; 2: Might go fishing; 3: Usually cancel fishing; 4: Usually go fishing - ImpactCalmWeather (part of “How will these factors influence your fishing?”):
0: Doesn’t matter; 1: Might cancel fishing; 2: Might go fishing; 3: Usually cancel fishing; 4: Usually go fishing - ImpactColdWeather (part of “How will these factors influence your fishing?”):
0: Doesn’t matter; 1: Might cancel fishing; 2: Might go fishing; 3: Usually cancel fishing; 4: Usually go fishing - ImpactLowAirPressure (part of “How will these factors influence your fishing?”):
0: Doesn’t matter; 1: Might cancel fishing; 2: Might go fishing; 3: Usually cancel fishing; 4: Usually go fishing - HouseholdSize (“How many people live in your household, including yourself?”):
0: 1 person; 1: 2 persons; 3: >2 persons - Education (“What is the highest level of education you have completed?”):
0: 12th grade or less; 1: High school graduate; 2: College graduate; 3: Some college / Technical training; 4: University degree; 5: Post graduate degree (Masters or Doctorate) - ImpactFishingRegs (“Do fishing regulations (like fish size limits, bag size limits) influence your choice of water body?”):
0: Not important; 1: Prefer with fish size and bag size limitations; 2: Prefer with fish size limitations; 3: Prefer with bag size limitations; 4: Prefer with catch-and-release; 5: Prefer without regulations - Status (“What is your marital status?”):
0: Single; 1: Married; 2: Divorced/separated; 3: Widowed - Income (“What is your total combined family income for the past 12 months?”):
0: >$150,000; 1: $100,000-$150,000; 2: $60,000-$100,000; 3: $30,000-$60,000; 4: <$30,000 - PlatformFishingTrips (“Where do you usually record your fishing trip?”):
0: None; 1: App, 2: Website - ImpactCovid19Fishing (“Did Covid-19 affect your fishing activity?”):
0: Didn’t change; 1: More fishing; 2: Less fishing - ImpactCovid19Distance (“Did Covid-19 affect the distances you traveled to go fishing?”):
0: Didn’t change; 1: Closer to home; 2: Further from home - ImpactDistance (“Does the distance you have to travel influence your choice of the water body?”:
TRUE / FALSE - Age (“How old are you?”):
0: <16 years; 1: 16-25 years; 2: 26-35 years; 3: 36-45 years; 4: 46-55 years; 5: 56-65 years; 6: 66-75 years; 7: >75 years - Gender (“What is your gender?”):
0: Male; 1: Female - FishingSkills (“How would you classify your fishing skills?”):
0: Beginner; 1: Intermediate; 2: Expert - FishingProvince (“In which province do you fish the most?”):
0: BC; 1: ON; 2: AB; 3: QB; 4: NB; 5: SK; 6: MT; 7: NS; 8: NL; 9: TT; 10: PEI - ProvinceResidence (“What is your postal code?”):
0: BC; 1: ON; 2: AB; 3: QB; 4: NB; 5: SK; 6: MT; 7: NS; 8: NL; 9: TT; 10: PEI - FishingExperience (“How many years have you been fishing?”):
0: <33 years; 1: 33-49 years; 2: >=50 years - FishingReason_Relaxation (“What are your primary reasons you go fishing?”):
TRUE / FALSE - FishingReason_Enjoyment (“What are your primary reasons you go fishing?”):
TRUE / FALSE - FishingReason_Social (“What are your primary reasons you go fishing?”):
TRUE / FALSE - FishingReason_Food (“What are your primary reasons you go fishing?”):
TRUE / FALSE - FishingReason_Sport (“What are your primary reasons you go fishing?”): TRUE / FALSE
- FishingReason_Outside (“What are your primary reasons you go fishing?”):
TRUE / FALSE - FishingReason_Competition (“What are your primary reasons you go fishing?”):
TRUE / FALSE - UseAA_Maps (“What do you find Angler’s Atlas helpful for?”):
TRUE / FALSE - UseAA_Species (“What do you find Angler’s Atlas helpful for?”):
TRUE / FALSE - UseAA_Regs (“What do you find Angler’s Atlas helpful for?”):
TRUE / FALSE - UseAA_Logbook (“What do you find Angler’s Atlas helpful for?”):
TRUE / FALSE - UseAA_Events (“What do you find Angler’s Atlas helpful for?”):
TRUE / FALSE - UseAA_Posts (“What do you find Angler’s Atlas helpful for?”):
TRUE / FALSE
File: Create_Evaluate_BN.R
Description:
This supplementary file contains the R code used to create the Bayesian Network as part of the study “Analyzing recreational fishing effort - Gender differences and the impact of Covid-19”.
Human subjects data
The dataset shows not actual survey responses but exemplary data, as participants consented to their data being used solely for the purposes of the related study. This means the dataset was artificially created for demonstration purposes - some columns were randomly shuffled, and the content does not reflect real individual answers.
The study was reviewed and approved by the Research Ethics Board of the Alberta Research Information Services (ARISE, University of Alberta), study ID MS5_Pro00102610.